Use of a progressive compression encoding of physiologic waveform data in an implantable device to support discontinuing transmission of low-value data

ABSTRACT

An external data retrieval apparatus receives a low resolution version of a physiological signal from an active implantable medical device and determines if the physiological signal represents a clinically significant event. The apparatus provides an indication of such determination to the implantable medical device. If the physiological signal does represent a clinically significant event, the apparatus receives a full download of the physiological signal from the implantable device.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a divisional application of U.S. patent applicationSer. No. 14/270,212, filed May 5, 2014, now U.S. patent Ser. No.10,231,621 for “Use of a Progressive Compression Encoding of PhysiologicWaveform Data in an Implantable Device to Support DiscontinuingTransmission of Low-Value Data.”

TECHNICAL FIELD

The present disclosure relates generally to transmission of data byactive implantable medical devices, and more particularly, toapparatuses and methods for optimizing the transmission of data fromactive implantable medical devices.

BACKGROUND

Modern active implantable medical devices, such as neurostimulators,pacemakers, and ICDs, are capable of not only monitoring patientcondition and delivering therapy, but are capable of storing detaileddata and diagnostics relating to a patient's condition for laterretrieval. Analysis of this data can improve patient care dramatically,and allow fine-tuning the performance of the implantable devices byprogramming them with new operational parameters. Interrogation of animplantable medical device allows data stored in the device to beretrieved by an external device. After analysis, reprogramming thedevice allows its performance to be optimized based on the interrogateddata.

Often it is desirable to store large quantities of data in theimplantable device until such time as the data can be transmitted fromthe implantable device to external equipment such as a physicianprogrammer or a home data monitor. Once the physiologic data has beenretrieved by the external equipment it is often incorporated into datarepository and made available for display and analysis. The resourcesavailable in an implantable device are often very limited. For example,the memory resources aboard an implantable device are limited by thesmall physical size constraints imposed on the design. Only physicallysmall and low power memory media are practical for this use. Typically,this limits the design to relatively small storage capacity CMOS staticRAM or similar devices.

The power source for implantable devices is often a small primary cell(non-rechargeable battery). The usable service life of an implantabledevice is typically determined by how quickly the battery is depleted.When the battery is depleted the usable service life is over. Minimizingthe duration of high power activities such as telemetry reduces the rateof battery depletion and so increases useful service life.

Implantable medical device systems often include a home data monitor.This provides the opportunity to upload physiologic data convenientlyand often. This reduces the demand for memory space onboard theimplantable device by affording opportunities to retrieve the contentsof this memory often. However, the home data monitor also increases thedemand for transporting large quantities of data over telemetry toexternal equipment. This increased telemetry activity increases the rateof battery depletion thereby reducing the useable service life for theimplantable device.

It would be desirable to provide mechanisms that optimize the retrievalof patient data in a manner that reduces implantable medical deviceenergy consumption and conserves memory space. The concepts disclosedbelow address these needs and others.

SUMMARY

In one implementation, an external data retrieval apparatus receives alow resolution version of a physiological signal from an activeimplantable medical device and determines if the physiological signalrepresents a clinically significant event. The apparatus provides anindication of such determination to the implantable medical device. Ifthe physiological signal does represent a clinically significant event,the apparatus receives a full download of the physiological signal fromthe implantable device.

In another implementation, an implantable medical device obtains datarepresentative of a physiological signal sensed by the implantablemedical device, and transmits data corresponding to a low resolutionversion of the physiological signal to an external data retrievaldevice. The device subsequently receives an indication from the externaldata retrieval device as to whether the physiological signal representsa clinically significant event; and transmits data corresponding to ahigh resolution version of the physiological signal when the signalrepresents a clinically significant event.

It is understood that other aspects of apparatuses and methods willbecome readily apparent to those skilled in the art from the followingdetailed description, wherein various aspects of apparatuses and methodsare shown and described by way of illustration. As will be realized,these aspects may be implemented in other and different forms and itsseveral details are capable of modification in various other respects.Accordingly, the drawings and detailed description are to be regarded asillustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

Various aspects of apparatuses and methods will now be presented in thedetailed description by way of example, and not by way of limitation,with reference to the accompanying drawings, wherein:

FIG. 1 is a schematic illustration of a patient's head showing theplacement of an implantable medical device;

FIG. 2 is a block diagram of a system for providing communicationbetween local medical devices and remote system components;

FIG. 3 is a block diagram of an implantable medical device;

FIG. 4 is a block diagram of a data retrieval apparatus;

FIG. 5 is an illustration of an ECOG waveform of a developing seizure inan epileptic patient.

FIG. 6 includes illustrations of different stages of ECOG waveformanalysis involved in the use of ECOG power to trigger full ECOGdownload.

FIG. 7 includes illustrations of a seizure onset (panel A), andcorresponding power spectral densities (panel B).

FIG. 8 includes illustrations of an ECOG segment transformed into apower spectral density.

FIG. 9 further illustrates this embodiment.

FIG. 10 includes illustrations of several ECOGs from an epilepsy patientare displayed in low resolution thumbnail mode.

FIG. 11 is an illustration of an uncompressed, full resolution ECOGwaveform.

FIG. 12 is an illustration of a low resolution version of the waveformfrom FIG. 11.

FIG. 13 is an illustration of a plot of the absolute difference betweenthe data presented in FIG. 11 and FIG. 12.

FIG. 14 is a histogram of the data presented in FIG. 13.

FIG. 15 is a flow chart of a method of retrieving data from animplantable medical device.

FIG. 16 is a flow chart of a method of data transmission by animplantable medical device;

FIG. 17 is a hardware implementation of a data retrieval apparatus.

FIG. 18 is a diagram of an exemplary hardware implementation of animplantable medical device.

DETAILED DESCRIPTION

Various aspects of the disclosure will be described more fullyhereinafter with reference to the accompanying drawings. This disclosuremay, however, be embodied in many different forms by those skilled inthe art and should not be construed as limited to any specific structureor function presented herein. Rather, these aspects are provided so thatthis disclosure will be thorough and complete, and will fully convey thescope of the disclosure to those skilled in the art. Based on theteachings herein, one skilled in the art should appreciate that thescope of the disclosure is intended to cover any aspect of thisdisclosure, whether implemented independently of or combined with anyother aspect of the disclosure. For example, an apparatus may beimplemented or a method may be practiced using any number of the aspectsset forth herein. In addition, the scope of the disclosure is intendedto cover such an apparatus or method which is practiced using otherstructure and/or functionality in addition to or instead of otheraspects of this disclosure. It should be understood that any aspect ofthe disclosure disclosed herein may be embodied by one or more elementsof a claim.

The concepts disclosed may be implemented in hardware or software thatis executed on a hardware platform. The hardware or hardware platformmay be a general purpose processor, a digital signal processor (DSP), anapplication specific integrated circuit (ASIC), a field programmablegate array (FPGA) or other programmable logic component, discrete gateor transistor logic, discrete hardware components, or any combinationthereof, or any other suitable component designed to perform thefunctions described herein. A general-purpose processor may be amicroprocessor, but in the alternative, the processor may be anyconventional processor, controller, microcontroller, or state machine. Aprocessor may also be implemented as a combination of computingcomponents, e.g., a combination of a DSP and a microprocessor, aplurality of microprocessors, one or more microprocessors in conjunctionwith a DSP, or any other such configuration.

Software shall be construed broadly to mean instructions, instructionsets, code, code segments, program code, programs, subprograms, softwaremodules, applications, software applications, software packages,routines, subroutines, objects, executables, threads of execution,procedures, functions, etc., whether referred to as software, firmware,middleware, microcode, hardware description language, or otherwise. Thesoftware may reside on a computer-readable medium. A computer-readablemedium may include, by way of example, a magnetic storage device (e.g.,hard disk, floppy disk, magnetic strip), an optical disk (e.g., compactdisk (CD), digital versatile disk (DVD)), a smart card, a flash memorydevice (e.g., card, stick, key drive), random access memory (RAM), readonly memory (ROM), programmable ROM (PROM), erasable PROM (EPROM),electrically erasable PROM (EEPROM), a general register, or any othersuitable non-transitory medium for storing software.

As mention above, an implantable medical device (IMD) such as apacemaker, implantable defibrillator, or neurostimulator stores datathat are useful for assessing patient medical status and for determiningthe operational status of the implantable medical device. However, theamount of memory present in the implantable medical device is limited,so eventually the implantable medical device may stop storing data, ormay need to overwrite older data to store new data. The term “overwrite”is used herein to describe data loss resulting from limited memory. Toavoid overwrite, it is desirable to have a home appliance that canretrieve data from the implantable medical device between office visitsin the patient's home. Such a home appliance, hereafter referred to as adata retrieval apparatus (DRA), would ideally use radio frequency (RF)telemetry to retrieve data transcutaneously from the implantable medicaldevice when the patient is in close proximity. The data retrievalapparatus could be a standalone device that the patient would bring totheir physician for read-out, or it could be internet connected to acentral database. Ideally the data retrieval apparatus would have atelemetry range long enough for it to be placed in a convenient locationwhere it could establish the telemetry link on a periodic basis withoutpatient intervention. The methods and apparatuses described herein (1)automate the setup process of the data retrieval apparatus for both thepatient and physician, (2) avoid data overwrite, and (3) minimize theenergy consumed by the implantable medical device when transmitting datato the data retrieval apparatus. Automation of the setup process reducesphysician workload. Avoiding data overwrite improves patient assessmentand care. Reducing energy consumed by the implantable medical deviceduring data transmission increases the life of the implantable medicaldevice's battery and reduces the frequency of implantable medical devicereplacement surgical procedures, which in turn lowers surgicalcomplications and reduces total medical costs.

With reference to FIG. 1, an exemplary implantable medical device 102 isshown implanted in a patient 104. In one configuration, the implantablemedical device 102 includes a small self-contained brainwave detectingdevice. As the term is used herein, a brainwave detecting or recordingdevice is a device capable of detecting or predicting ictal activity (orother neurological events) for providing data useful in the diagnosis ofa neurological disorder. Further, the term recording device, as usedherein, is a device that can either record neurological signals, such asEEG signals, or detect and analyze EEG signals and create a log of suchan analysis.

The implantable medical device 102 may be configured to detect orpredict neurological events that have a representative electrographicsignature. For example, the implantable medical device 102 may beresponsive to epileptic seizures. It should, however, be recognized thatit is also possible to respond to other types of neurological disorders,such as movement disorders (e.g. the tremors characterizing Parkinson'sdisease), migraine headaches, chronic pain, and neuropsychiatricdisorders such as depression.

With reference to FIG. 2, an exemplary patient monitoring system 200 isillustrated. The patient monitoring system 200 includes local componentsand remote components that communicate through a communications network202, such as the Internet. Local components are located in the vicinityof the patient, such as the patient's residence, and may include animplantable medical device 204, and a local device 206, referred toherein as a data retrieval apparatus. Remote components are located asignificant distance from the patient, such as at a hospital or careprovider's office. Remote components may include, for example, aprogrammer 208, a network server 210 and a database 212.

The programmer 208 is typically operated by medical personnel (such asthe patient's treating physician) to control the operation of theimplantable medical device 204. In general terms, the programmer 208functions as a clinical interface to the implantable medical device 204,allowing the implantable medical device parameters to be modified, andfor data and/or program code to be uploaded from and downloaded to theimplantable medical device.

The database 212 serves as a centralized data repository for all datarelevant to the operation of the system 200, and may include clinicaldata, program code, and more. The network server 210 acts as the primaryinterface between the database 212 and other devices attached to thecommunications network 202. Although it might be possible andadvantageous in certain circumstances to communicate directly with thedatabase 212, it is generally preferable to configure the network server210 to receive queries, perform necessary authentication, access thedatabase 212, and respond as necessary, thereby reducing the processingload on the database and also reducing the exposure of the database tonetwork traffic (thereby improving security).

The data retrieval apparatus 206 is configured to receive data fromremote components through the communications network 202 and provide itto the implantable medical device 204. Such data may include, forexample, program code or instructions from a programmer 208 that affectthe operation of the implantable medical device 204. The data retrievalapparatus 206 is also configured to retrieve data from the implantablemedical device 204 and to forward it to one or more of the remotecomponents. As described further below, communication between the dataretrieval apparatus 202 and the implantable medical device 204 iswireless, and may be in the form of short-range telemetry by inductivecoupling or long-range telemetry by RF communications.

An overall block diagram of an implantable medical device 304 used formeasurement, detection, and treatment is illustrated in FIG. 3. Insidethe housing of the device 304 are several subsystems making up a controlmodule 310. The control module 310 is capable of being coupled to aplurality of electrodes 312, 314, 316, and 318 for sensing andstimulation. Although four electrodes are shown in FIG. 3, it should berecognized that any number is possible.

The electrodes 312-318 are connected to an electrode interface 320.Preferably, the electrode interface is capable of selecting eachelectrode as required for sensing and stimulation; accordingly theelectrode interface is coupled to a detection subsystem 322 and astimulation subsystem 324. The electrode interface also may provide anyother features, capabilities, or aspects, including but not limited toamplification, isolation, and charge-balancing functions, that arerequired for a proper interface with neurological tissue and notprovided by any other subsystem of the implantable medical device 304.

The detection subsystem 322 includes an EEG analyzer function. The EEGanalyzer function is adapted to receive EEG signals from the electrodes312-318, through the electrode interface 320, and to process those EEGsignals to identify neurological activity indicative of a seizure, anonset of a seizure, or a precursor to a seizure. One way to implementsuch EEG analysis functionality is disclosed in detail in U.S. Pat. No.6,016,449 to Fischell et al., which is hereby incorporated by reference.The detection subsystem may optionally also contain further sensing anddetection capabilities, including but not limited to parameters derivedfrom other physiological conditions (such as electrophysiologicalparameters, temperature, blood pressure, etc.).

The stimulation subsystem 324 is capable of applying electricalstimulation to neurological tissue through the electrodes 312-318. Thiscan be accomplished in any of a number of different manners. Forexample, it may be advantageous in some circumstances to providestimulation in the form of a substantially continuous stream of pulses,or on a scheduled basis. Preferably, therapeutic stimulation is providedin response to abnormal events detected by the EEG analyzer function ofthe detection subsystem 322. As illustrated in FIG. 3, the stimulationsubsystem 324 and the EEG analyzer function of the detection subsystem322 are in communication; this facilitates the ability of stimulationsubsystem 324 to provide responsive stimulation as well as an ability ofthe detection subsystem 322 to blank the amplifiers while stimulation isbeing performed to minimize stimulation artifacts. It is contemplatedthat the parameters of the stimulation signal (e.g., frequency,duration, waveform) provided by the stimulation subsystem 324 would bespecified by other subsystems in the control module 310.

Also in the control module 310 is a memory subsystem 326 and a centralprocessing unit (CPU) 328, which can take the form of a microcontroller.The memory subsystem 326 is coupled to the detection subsystem 322(e.g., for receiving and storing data representative of sensed EEGsignals and evoked responses), the stimulation subsystem 324 (e.g., forproviding stimulation waveform parameters to the stimulation subsystem),and the CPU 328, which can control the operation of the memory subsystem326. In addition to the memory subsystem 326, the CPU 328 is alsoconnected to the detection subsystem 322 and the stimulation subsystem324 for direct control of those subsystems. A compression module (notshown) may be located between the detection subsystem 322 and the memorysubsystem 326. The compression module is configured to compress data,e.g., ECOG data, sensed by the detection subsystem 322 prior to storagein the memory subsystem 326.

The memory subsystem 326 may include one or more types of memory,including for example, random access memory (RAM), read only memory(ROM), and non-volatile memory (NVM). As explained further below, withinone or more of the types of memory, such as RAM, there may be sectionsof memory reserved for the following: 1) EEG waveform data (storedECOG's), 2) detailed event data regarding detection activity, 3)long-term histogram data on detections, and 4) device diagnosticinformation (battery voltage, lead impedance, radio usage, etc)

Also provided in the control module 310, and coupled to the memorysubsystem 326 and the CPU 328, is a communication subsystem 330. Thecommunication subsystem 330 enables communication between theimplantable medical device 204 (FIG. 2) and the outside world, e.g., thedata retrieval apparatus 206 (FIG. 2). The communication subsystem 330may include a telemetry coil (which may be situated outside of thehousing) enabling short-range transmission and reception of signals, toor from the implantable medical device 204, via inductive coupling. Thecommunication subsystem 330 may also include a transceiver and one ormore antennas for long-range telemetry by an RF communications link withthe implantable medical device 204.

Rounding out the subsystems in the control module 310 are a power supply332 and a clock supply 334. The power supply 332 supplies the voltagesand currents necessary for each of the other subsystems. The clocksupply 334 supplies substantially all of the other subsystems with anyclock and timing signals necessary for their operation.

While the memory subsystem 326 is illustrated in FIG. 3 as a separatefunctional subsystem, the other subsystems may also require variousamounts of memory to perform the functions described above and others.Furthermore, while the control module 310 is preferably a singlephysical unit contained within a single physical enclosure, namely thehousing, it may comprise a plurality of spatially separate units eachperforming a subset of the capabilities described above. Also, thevarious functions and capabilities of the subsystems described above maybe performed by electronic hardware, computer software (or firmware), ora combination thereof.

Referring now to FIG. 4, a block diagram representing a data retrievalapparatus 406 is set forth in detail. The data retrieval apparatus 406includes a general-purpose or special-purpose computer programmed oradapted for use as described herein. The data retrieval apparatus 406includes a wide area communications interface 412 for communicationswith the communications network 202 (FIG. 2), and a local areacommunications interface 414 for communications with the implantablemedical device 204. The wide area communications interface 412 may be,for example, an Internet connection. The local area communicationsinterface 414 may be an inductive short-range telemetry system includingan inductive coil, or a long-range RF telemetry system including an RFantenna. The method and apparatuses disclosed herein are primarilydirected to RF telemetry communications. Preferably, both the wide areacommunications interface 412 and the local area communications interface414 are capable of bi-directional communications.

The data retrieval apparatus 406 is controlled by a CPU 416. The CPU iscoupled, either directly or through a bus controller, to the wide areacommunications interface 412, the local area communications interface414, a memory subsystem 418 for programming and short-term storage, astorage subsystem 420 (which might include a hard drive, flash memory,and other non-volatile storage), and an input/output subsystem 422 usedto pass information to and receive information from a user. The memorysubsystem 418 may include ROM, dynamic RAM, and other random-accessmemory. The storage subsystem 420 may include a hard drive, flashmemory, and other non-volatile storage.

The operation of the data retrieval apparatus 406 is controlled by apower supply 424 and a clock supply 426. The power supply 424 typicallyincludes batteries. Alternatively, the data retrieval apparatus 406 mayreceive power from an AC outlet. A combination of the two sources mightalso be used. The clock supply 426 supplies substantially all of theother subsystems of the network unit with any clock and timing signalsnecessary for their operation.

As with the implantable medical device 304 (FIG. 3) described above,while the memory subsystem 418 is illustrated in FIG. 4 as a separatefunctional subsystem, the other subsystems may also require variousamounts of memory to perform the functions described herein and others.Furthermore, while the data retrieval apparatus 406 is preferably asingle physical unit contained within a single physical enclosure,namely the housing, it may comprise a plurality of spatially separateunits each performing a subset of the capabilities described herein.

The various functions and capabilities of the subsystems of the dataretrieval apparatus 406 described above may be performed by electronichardware, computer software, or firmware, or a combination thereof. Theillustration of FIG. 4 shows several of the major functional subsystemspresent in a data retrieval apparatus consistent with the invention.However, in many computing systems, other functional subsystems andmodules are present that are not necessarily reflected in FIG. 4.Moreover, a data retrieval apparatus 406 may integrate two or more ofthe above-referenced subsystems. For example, the wide areacommunications interface 412 and the local area communications interface414 might be adapted into a single subsystem if efficiencies resultthere from. Accordingly, FIG. 4 is for purposes of illustration only,and does not necessarily reflect the actual configuration of the dataretrieval apparatus. It is, however, considered to be representative.

As noted above, active implantable medical devices that monitor andrecord physiologic signals can generate and store large quantities ofdata. Memory and power resources available in an implantable device,however, are often very limited. Regarding memory, such resources aboardan implantable device are limited by the small physical size constraintsimposed on the design. Only physically small and low power memory mediaare practical for this use. Typically, this limits the design torelatively small storage capacity CMOS static RAM or similar devices.Regarding power, such resource for implantable devices is often a smallprimary cell (non-rechargeable battery). The usable service life of animplantable device is typically determined by how quickly the battery isdepleted. When the battery is depleted the usable service life is over.

Implantable systems often include a home data monitor. The monitorprovides the opportunity to upload physiologic data conveniently andoften, and reduces the demand for memory space onboard the implantabledevice by affording opportunities to retrieve the contents of memoryoften. However, the home data monitor also increases the demand fortransporting large quantities of data over telemetry to externalequipment. This increased telemetry activity increases the rate ofbattery depletion thereby reducing the useable service life for theimplantable device.

Disclosed herein are techniques that minimize the duration of high poweractivities, such as telemetry of physiologic data from the implanteddevice to the external equipment, to thereby reduce the rate of batterydepletion and increase device longevity. The disclosed techniques alsoconserve memory space by providing compression of the physiologic dataas it is being stored.

Well known progressive encoding systems (e.g., JPEG) are often used forstoring large image files such as those from digital cameras.Progressive encoding allows an image to be displayed at low resolutionafter only a small portion of the image file has been retrieved forexample over a slow data link. Thus, a low resolution version of theimage can be displayed very quickly after only a small portion of datahas been retrieved. As more data slowly streams in, the image can bedisplayed in higher and higher resolution until the download iscomplete.

In systems and methods disclosed herein, physiologic waveform (e.g.,ECOG waveform) data recorded by an active implantable medical device iscompressed by the device using a progressive encoding system, e.g.,JPEG. During a telemetry session with an external apparatus, theimplantable device transmits to the external apparatus, a portion of anencoded file representing a low resolution version of a physiologicwaveform. Once uploaded to the external apparatus, the apparatus has alow resolution version of the waveform available for analysis.Algorithms within the external apparatus make a determination of thevalue of the waveform. If the waveform is deemed of interest, orvaluable, the upload is allowed to complete until a full resolutionversion of the waveform is received. If the waveform is not deemedvaluable, the upload is discontinued. Discontinuing the upload ofwaveforms that are not valuable reduces the duration of the telemetryactivity which in turn reduces the rate of battery depletion and extendsthe usable implant service life.

A waveform could be deemed valuable if even in the low resolutionversion is determined to be novel or different from other waveformscollected from the same implantable device. High value may be assignedto waveforms that result directly from a patient action such as theapplication of the magnet to the implantable device, or to waveformsthat fit other predetermined criteria. A waveform could be considered oflow value if the low resolution version is determined to be similar toother waveforms already collected. Even though the uploading of the lowvalue waveform is discontinued the low resolution version of thewaveform may be stored in the central data repository along withdiagnostic information explaining why the full resolution waveform wasnot retrieved from the implantable device.

Full download is desired for an ECOG that represents a clinicallysignificant event. ECOG characteristics that can indicate clinicallysignificant events include significant changes in signal amplitude andspectral content, both of which can result in ECOG power changes.

Total Power Change

In one configuration, systems and methods determine if a low resolutionECOG represents a clinically significant event based on total powerchange in the ECOG signal when a seizure develops and spreads. FIG. 5 isan illustration of an ECOG waveform of a developing seizure in anepileptic patient. In FIG. 5, the power present in the signal increasessignificantly from point A to point B.

The y-axis of the ECOG signal is amplified voltage and is proportionalto the intrinsic ECOG voltage at the output from a non-saturated linearamplifier. Instantaneous power is the product of the ECOG voltage andECOG current. ECOG current is related to the ECOG voltage by the sourceimpedance, which can be measured, but typically is not precisely known.However, the source impedance should be constant over the desiredtimeframes so ECOG power can be approximated by the square of the ECOGvoltage.

FIG. 6 includes illustrations of different stages of ECOG waveformanalysis involved in the use of ECOG power to determine if a lowresolution ECOG waveform represents a clinically significant event so asto trigger full ECOG download. FIG. 6 illustrates an embodiment thatuses ECOG power to trigger full ECOG download. In panel A the lowresolution ECOG is shown. Using standard techniques known to those ofordinary skill in the art, the ECOG waveform is rectified and thensquared to show a signal proportional to the ECOG power as shown inpanel B. Using a series of summation registers labeled S1 to S6 in panelB, the power within time segments is determined for the time periodscorresponding to the summation registers S1 thru S6. These registerdurations would typically be 1 to 30 seconds in duration. The summationregisters may overlap in time in some embodiments to produce a smoothingeffect if desired, but are shown without time overlap in FIG. 6. In theevent the data are sampled at fixed intervals, the summed areas may becalculated by summing the sampled values, which produces computationalefficiencies.

To determine if the low resolution waveform represents a clinicallysignificant event so as to trigger a full ECOG download, the summationregister values are compared to a criterion, such as a threshold. If oneor more of the register values exceeds the threshold, the low resolutionwaveform is deemed to represent a clinically significant event, and fulldownload of the waveform is triggered. In one configuration, thethreshold may be based on the segment power exceeding a given level. Inanother configuration, the threshold may be based on the difference inthe segment power between adjacent segments exceeding a given level. Forexample, if the difference between the segment power of segment S1 andsegment S2 exceeds a difference threshold, then the low resolutionwaveform is deemed to represent a clinically significant event.Furthermore, although the segment power is shown as increasing in theexample of FIG. 6, the threshold could be negative with power depletionsbeing the triggering event.

The threshold for determining if a low resolution waveform represents aclinically significant event and triggering full ECOG download could befixed or may be a percentage above a background trend. In oneconfiguration, the running average of several summation registers at thebeginning of each ECOG may be used as a baseline. Abrupt changes withineach ECOG, relative to the baseline, would result in a determination ifthat low resolution waveform represents a clinically significant event,and trigger full ECOG download. Use of a running average is beneficialin that it allows for biocalibration of the threshold based on inherentbackground power levels which vary based on neural state (asleep,drowsy, awake, alert, etc). In this manner the threshold for anindividual ECOG could be set as a multiple (100%, 200%, etc.) of theaverage segment power or segment power differences observed at thebeginning of that ECOG.

In another configuration, the external apparatus may be configured toalways fully retrieve a fixed number of ECOGs (1, 2, etc.). In thiscase, the external apparatus derives a power metric, e.g., segment powerlevel or segment power difference, for each available low-resolutionECOG that is being considered for retrieval, and selects for fulldownload, a number of low resolution ECOGs corresponding to the fixednumber based on the respective metrics. For example, if the externalapparatus is configured to retrieve 3 full resolution ECOGs perinterrogation session, the ECOGs with the three highest segment powersor segment power differences are selected.

The power threshold could also be determined based on measured changesdetermined during prior ECOG retrieval sessions. For example, theexternal apparatus could have an evolving threshold that triggers fulldownload for ECOGs that exhibit maximum segment power or maximum segmentpower difference that exceeds a certain percentage of observations forall prior sessions. In this embodiment, the external apparatus tracksall ECOG maximum segment power or maximum segment difference values overall retrieval sessions, and then sets the threshold to a percentage ofthe prior observations (80%, 90%, etc.). Metrics, e.g., maximum segmentpower or maximum segment power difference, are derived for new ECOGs andcompared to the threshold. If the metric of the new ECOG exceeds thecorresponding metric of the threshold percentage of the prior ECOGs, thenew ECOG is determined to be a clinically significant event. Forexample, if the threshold percentage is 80% and the metric of the newECOG is greater than the same metric of 80% of the prior ECOGs, the newECOG is clinically significant, and a full download of the new ECOG istriggered. As new ECOGs are presented, the external apparatus adjuststhe threshold. In this manner the ECOGs with the most powerful segmentsor segment differences would always be fully retrieved, which presumablywould have the highest clinical significance.

Spectral Band Power Content

Another method that may be useful for determining if a low resolutionwaveform represents a clinically significant event involves assessingpower changes within spectral bands. FIG. 7 includes illustrations of aseizure onset (panel A), and corresponding power spectral densities(panel B). FIG. 7 shows a seizure onset (panel A) that is characterizedby an abrupt shift in spectral content. Segment 1 shows higher spectralpower at the lower frequencies, as illustrated by the Power SpectralDensity (PSD) plot in panel B. Segment 2 shows a power peak at higherfrequencies as shown by the PSD plot in panel C. Because these spectralpower shifts can be indicative of ictal onset, they may be useful fordetermining ECOGs of clinical interest. Because the ECOGs used in thisanalysis would be frequency limited by the under-sampling inherent inthe lower resolution form, this method may be limited to waveforms wherefrequency content changes are evident at the lower sampled rate, orwhere sufficient higher frequency power content is aliased to lowerfrequencies.

FIG. 8 includes illustrations of an ECOG segment transformed into apower spectral density (PSD). The transformation may be made usingstandard techniques known to one of ordinary skill in the art. The powerpresent within discrete frequency bands, such as those commonly used inclinical analysis (D=Delta, T=Theta, A=Alpha, B=Beta), are calculated byintegrating the PSD within the discrete bandwidths to result in a smallseries of values representative of bandwidth power for each ECOGsegment. The number of bandwidths would be typically 2 to 8.

FIG. 9 includes illustrations of an ECOG segment transformed into anumber of segmented spectral analyses segments. Panel A shows the lowresolution ECOG, which is broken up into a series of spectral analysissegments labeled S1 thru S6 in panel B. These spectral analysis segmentsare typically 1 to 30 seconds in duration. The spectral analysissegments may overlap in time in some embodiments to produce a smoothingeffect if desired, but are shown without time overlap in FIG. 9. Foreach segment the PSD is calculated and the integrated band powers aredetermined (panel C). A low resolution waveform is deemed to represent aclinically significant event and full ECOG download is triggered whenthe band power of a frequency band satisfies a criterion correspondingto that particular frequency band. The criterion may be a threshold bandpower level and the criterion may be considered satisfied when the bandpower in exceeds the threshold. The criterion may be a threshold bandpower difference that is satisfied when the difference in the band powerof a particular frequency between adjacent segments exceeds a giventhreshold. Furthermore, although the band power is shown as increasingin the example of FIG. 9, the threshold could be negative with powerdepletions being indicative of a clinically significant event.

Determining the band of interest may be performed in several ways. Inone embodiment, a central user such as the programming physician couldindicate the bandwidth to use based on detailed ECOG examination. Inanother embodiment the external apparatus could use certain operatingpoints to collect ECOGS, which were then presented to the central userfor comparison. For example, the external apparatus could collect aseries of ECOGs with the greatest power change in each of the severalbandwidths, and the user could indicate which bandwidth best triggeredmost meaningful ECOG download. In another embodiment, the power changespresent in the different bandwidths could be compared to seizure diarydata collected from the patient. These data could be collected using anon-line entry system, or by a device feature such as a magnetic fieldsensor that could trigger when the patient placed a magnet on theimplanted device.

Once the bandwidth of interest is determined, the criterion fordetermining if a low resolution waveform represents a clinicallysignificant event may be determined in several ways. In oneconfiguration, the running average of several summation spectralanalysis segments at the beginning of each ECOG may be used as abaseline. Abrupt changes within an ECOG, relative to the baseline, wouldbe indicative of a low resolution waveform that represents a clinicallysignificant event would trigger full ECOG download. An abrupt change inspectral power may correspond to a value or percentage above baseline.Use of a running average is beneficial in that it allows forbiocalibration of the threshold based on inherent background powerlevels which vary based on neural state (asleep, drowsy, awake, alert,etc). In this manner the band power or band power difference thresholdfor an individual ECOG could be set as a multiple (100%, 200%, etc.) ofthe baseline band power or baseline band power differences observed atthe beginning of that ECOG.

In another configuration, the external apparatus may be configured toalways fully retrieve a fixed number of ECOGs (1, 2, etc.). In thiscase, the external apparatus derives a power metric, e.g., band power orband power difference, for each available low-resolution ECOG that isbeing considered for retrieval, and selects for full download, a numberof low resolution ECOGs corresponding to the fixed number based on therespective metrics. For example, if the external apparatus is configuredto retrieve 3 full resolution ECOGs per interrogation session, the ECOGswith the three highest band powers or band power differences areselected.

The band power threshold could also be determined based on measuredchanges determined during prior ECOG retrieval sessions. For example,the external apparatus may have an evolving threshold that triggers fulldownload for ECOGs that exhibit band powers or band power differencethat exceed a certain percentage of observations for all prior sessions.In this embodiment, the external apparatus tracks all ECOG band power orband power difference values over all retrieval sessions, and then setsthe threshold to a percentage of the prior observations (80%, 90%,etc.). Metrics, e.g., band power or band power difference, are derivedfor new ECOGs and compared to the threshold. If the metric of the newECOG exceeds the corresponding metric of the threshold percentage of theprior ECOGs, the new ECOG is determined to be a clinically significantevent. For example, if the threshold percentage is 80% and the metric ofthe new ECOG is greater than the same metric of 80% of the prior ECOGs,the new ECOG is clinically significant, and a full download of the newECOG is triggered. As new ECOGs are presented, the external apparatusadjusts the threshold. In this manner the ECOGs with the most powerfulsegments or segment differences would always be fully retrieved, whichpresumably would have the highest clinical significance.

The selection of ECOG waveforms for full resolution upload may be basedon template matching. In this configuration, a low resolution waveformis evaluated and categorized based on how well it matches any number ofpre-specified template waveforms. A metric of how well a low resolutionwaveform fits a template may be scored based on a cross-correlationcalculation of the low resolution waveform and the template. If themetric satisfies a criterion, the physiological signal corresponding tothe low resolution version may be determined to represent a clinicallysignificant event.

The selection of ECOG waveforms for full resolution upload is optimizedto exhibit diversity. In this configuration, the intent is to presentthe physician with fully uploaded ECOG records that represent thevariety of ECOG types recorded from a given patient to contribute to thephysician's understanding of the patient's condition. This reduces thelikelihood that the physician would be presented with an artificiallyhomogenous set of ECOG records based on the selection criteria used forfull resolution uploads. In this embodiment priority for full resolutionupload is granted to any ECOG record having a low resolution versionthat exhibits different characteristics than the majority of ECOGrecords recently selected for full resolution upload. For example, ifthe most recent 10 ECOG records that were selected for full resolutionupload were so selected based on a sudden increase in signal power asdescribed above, then priority may be granted to the next ECOG recordthat displays a frequency shift or some other characteristic that is notrepresented in the set of recently fully uploaded ECOG records.

An implantable medical device may be configured to transmit compressedsignals or to transmit full resolution signals. The decision to transmitcompressed waveforms could be based on a programmed setting in theimplanted device, or it could be based on a setting in the datarepository that is communicated to a home data monitor. In the latercase the physician would have the option to remotely select compressedor non-compressed waveforms based on patient needs without altering theimplanted device software or programming.

FIG. 10 includes illustrations of several ECOGs from an epilepsy patientdisplayed in low resolution thumbnail mode. This figure shows thumbnailresolution images of ECOGs that convey events that are seizures. Itwould be clear to a physician specializing in the treatment of epilepsythat the first and last ECOGs are seizures. Furthermore, based onobservation the physician may determine that compressed waveforms areadequate to care for this patient and may elect to reduce energyconsumption by compressing all waveform data for transmission to enhancethe battery life of the implanted device. A decision to implementcompression of physiological waveform may be made if the programmedsettings for the implantable device have been stable for a long periodof time and the user has determined that compressed waveform data areadequate for diagnostic purposes and the battery longevity improvementthat results from reduced telemetry energy use from such compression isbeneficial for the patient.

FIG. 11 is an illustration of an uncompressed, full resolution ECOGwaveform. FIG. 12 is an illustration of a low resolution version of thewaveform from FIG. 11. FIG. 12 shows that a good representation of anECOG waveform can be viewed with only 1/5.26 (about 20%) of the dataused to represent the full waveform. Less than 20% of the data from FIG.11 was used to generate this plot. The compression ratio (CR) shown hereis 5.26.

FIG. 13 is an illustration of a plot of the absolute difference betweenthe data presented in FIG. 11 and FIG. 12. The plot of FIG. 13 allowsfor a visualization of the difference between the low resolution and thefull resolution data is to actually plot the difference. FIG. 13 showsthat more than 50% of the points are within 5 counts of the fullresolution waveform. More than 75% of the samples are within 10 counts.The difference between the data from FIG. 11 and FIG. 12 can also beexpressed as a histogram of the data presented in FIG. 13. This data ispresented in FIG. 14.

FIG. 15 is a flow chart of a method of retrieving data from animplantable medical device. The method may be performed by an externalapparatus, such as a programmer or remote home monitoring deviceconfigured to communicate with the implantable medical device. At step1502, the external apparatus receives a low resolution version of aphysiological signal from an active implantable medical device. The lowresolution signal may be a portion of a compressed version of aphysiological signal, e.g., ECOG, sensed by the implantable medicaldevice. The signal may be compressed using a progressive encodingtechnique, such as JPEG. The signal may be received by the externalapparatus by wireless telemetry, such as previously described withreference to FIG. 4.

At step 1504, the external apparatus determines if the physiologicalsignal represents a clinically significant event. The external apparatusmay process the signal to detect for a change in power in the lowresolution signal that is indicative of a clinically significant event.For example, the external apparatus may derive a power metric for thelow resolution signal, and compare the power metric to a criterion,e.g., a threshold, that when met serves as an indication of a clinicallysignificant event. In one implementation, the power metric may be asegmented power metric for a time segment of the low resolution signal.In this case, the criterion is met when the segmented power metricexceeds a power level threshold. In another implementation, the powermetric may be a difference between adjacent segmented power metrics,where each segmented power metric corresponding to a power metric in arespective time segment of the low resolution signal. In this case, thecriterion is met when the difference exceeds a power change threshold.

In another implementation, the power metric may be a frequency bandpower metric for a time segment of the low resolution signal. In thiscase, the criterion is met when the frequency band power metric exceedsits corresponding power level threshold. In yet another implementation,the power metric may be a difference between corresponding frequencyband power metrics of adjacent time segments of the low resolutionsignal. In this case, the criterion is met when the differences exceedsa power change threshold for the frequency band.

At step 1506, the external apparatus provides an indication of suchdetermination to the implantable medical device. For example, theexternal apparatus may transmit a trigger signal to the implantabledevice requesting a full download of the compressed file correspondingto the low resolution version. The trigger signal may be sent overwireless telemetry.

FIG. 16 is a flow chart of a method of data transmission. The method maybe performed by an active implantable medical device configured tocommunicate with an external apparatus. At step 1602, the device obtainsdata representative of a physiological signal sensed by the implantablemedical device. The device may sense physiological activity through oneor more electrodes and record data representative of the activity. Forexample, the device may record ECOG waveforms in a compressed format,such as JPEG.

At step 1604, the device transmits data corresponding to a lowresolution version of the physiological signal to an external dataretrieval device. The transmission may be in response to aninterrogation by the external apparatus. The low resolution version maycorrespond to a portion of the full recording of the physiologicalsignal sufficient to allow the external apparatus to determine whetherthe physiological signal represents a clinically significant event.

At step 1606, the device receives an indication from the external dataretrieval device as to whether the physiological signal represents aclinically significant event. For example, the external apparatus maytransmit a trigger signal to the implantable device requesting a fulldownload of the compressed file corresponding to the low resolutionversion. The trigger signal may be received by the device over wirelesstelemetry.

At step 1608, the device transmits data corresponding to a highresolution version of the physiological signal when the signalrepresents a clinically significant event. At step 1610, the devicerefrains from transmitting a high resolution version of thephysiological signal when the signal does not represent a clinicallysignificant event.

FIG. 17 is a diagram illustrating an example of a hardwareimplementation for a data retrieval apparatus 1706 that implements themethod of FIG. 15. The apparatus 1706 employs a processing system 1710.The processing system 1710 may be implemented with a bus architecture,represented generally by the bus 1724. The bus 1724 may include anynumber of interconnecting buses and bridges depending on the specificapplication of the processing system 1710 and the overall designconstraints. The bus 1724 links together various circuits including oneor more processors and/or hardware modules, represented by the processor1712, a receiving module 1714, a determining module 1716, an indicationmodule 1718, and a computer-readable medium 1722. The bus 1724 may alsolink various other circuits such as timing sources, peripherals, voltageregulators, and power management circuits, which are well known in theart, and therefore, will not be described any further.

The receiving module 1714 is configured to receive a low resolutionversion of a physiological signal from an active implantable medicaldevice. The determining module 1716 is configured to determine if thephysiological signal represents a clinically significant event. Theindication module 1718 is configured to provide an indication of suchdetermination to the implantable medical device.

The modules 1714, 1716 and 1718 may be software modules running in theprocessor 1712, resident/stored in the computer readable medium 1722,one or more hardware modules coupled to the processor 1712, or somecombination thereof. The processing system 1710 may be coupled to atransceiver 1724. The transceiver 1724 is coupled to one or moreantennas 1726. The transceiver 1724 provides a means for communicatingwith various other apparatus over a transmission medium, including forexample an implantable medical device. The transceiver 1724 receives asignal from the one or more antennas 1726, extracts information from thereceived signal, and provides the extracted information to theprocessing system 1710. In addition, the transceiver 1724 receivesinformation from the processing system 1710 and based on the receivedinformation, generates a signal to be applied to the one or moreantennas 1726.

The processing system 1710 includes a processor 1712 coupled to acomputer-readable medium 1722. The processor 1712 is responsible forgeneral processing, including the execution of software stored on thecomputer-readable medium 1722. The software, when executed by theprocessor 1712, causes the processing system 1710 to perform the variousfunctions described supra for any particular module. Thecomputer-readable medium 1722 may also be used for storing data that ismanipulated by the processor 1712 when executing software.

FIG. 18 is a diagram illustrating an example of a hardwareimplementation for an active implantable medical device 1804 thatimplements the method of FIG. 16. The device employs a processing system1810. The processing system 1810 may be implemented with a busarchitecture, represented generally by the bus 1824. The bus 1824 mayinclude any number of interconnecting buses and bridges depending on thespecific application of the processing system 1810 and the overalldesign constraints. The bus 1824 links together various circuitsincluding one or more processors and/or hardware modules, represented bythe processor 1812, a obtaining module 1814, a transmitting module 1816,a receiving module 1818, and a computer-readable medium 1822. The bus1824 may also link various other circuits such as timing sources,peripherals, voltage regulators, and power management circuits, whichare well known in the art, and therefore, will not be described anyfurther.

The obtaining module 1814 is configured to obtain data representative ofa physiological signal sensed by the implantable medical device. Thetransmitting module 1816 is configured to transmit data corresponding toa low resolution version of the physiological signal to an external dataretrieval device, and to subsequently transmit data corresponding to ahigh resolution version of the physiological signal when the signalrepresents a clinically significant event. The transmitting module isfurther configured to refrain from transmitting a high resolutionversion of the physiological signal when the signal does not represent aclinically significant event. The receiving module 1818 is configured toreceive an indication from the external data retrieval device as towhether the physiological signal represents a clinically significantevent.

The modules 1814, 1816 and 1818 may be software modules running in theprocessor 1812, resident/stored in the computer readable medium 1822,one or more hardware modules coupled to the processor 1812, or somecombination thereof. The processing system 1810 may be coupled to atransceiver 1824. The transceiver 1824 is coupled to one or moreantennas 1826. The transceiver 1824 provides a means for communicatingwith various other apparatus over a transmission medium, including forexample an external apparatus. The transceiver 1824 receives a signalfrom the one or more antennas 1826, extracts information from thereceived signal, and provides the extracted information to theprocessing system 1810. In addition, the transceiver 1824 receivesinformation from the processing system 1810 and based on the receivedinformation, generates a signal to be applied to the one or moreantennas 1826.

The processing system 1810 includes a processor 1812 coupled to acomputer-readable medium 1822. The processor 1812 is responsible forgeneral processing, including the execution of software stored on thecomputer-readable medium 1822. The software, when executed by theprocessor 1812, causes the processing system 1810 to perform the variousfunctions described supra for any particular module. Thecomputer-readable medium 1822 may also be used for storing data that ismanipulated by the processor 1812 when executing software.

This invention extends the usable service life of implantable devices byreducing the amount of data that must be retrieved from the implant overthe high power telemetry link.

Methods and apparatuses disclosed herein allow external equipment todetermine which physiological signals, e.g., ECOG waveform, are ofinterest. The external equipment has much greater computing power andsophistication than the implantable device. Allowing the externalequipment to determine which waveforms are of interest allows morecomplex decision making criteria to be used. Any one of several criteriadescribed above may be used to by the external equipment to determine ifa particular waveform is valuable enough to trigger a full download ofthe signal from the implantable device.

The various aspects of this disclosure are provided to enable one ofordinary skill in the art to practice the present invention. Variousmodifications to exemplary embodiments presented throughout thisdisclosure will be readily apparent to those skilled in the art, and theconcepts disclosed herein may be extended to other magnetic storagedevices. Thus, the claims are not intended to be limited to the variousaspects of this disclosure, but are to be accorded the full scopeconsistent with the language of the claims. All structural andfunctional equivalents to the various components of the exemplaryembodiments described throughout this disclosure that are known or latercome to be known to those of ordinary skill in the art are expresslyincorporated herein by reference and are intended to be encompassed bythe claims. Moreover, nothing disclosed herein is intended to bededicated to the public regardless of whether such disclosure isexplicitly recited in the claims. No claim element is to be construedunder the provisions of 35 U.S.C. § 112, sixth paragraph, unless theelement is expressly recited using the phrase “means for” or, in thecase of a method claim, the element is recited using the phrase “stepfor.”

What is claimed is:
 1. An implantable medical device comprising: atransceiver; a memory configured to store a full resolution version ofan electrographic waveform as a progressive encoded file; and at leastone processor coupled to the transceiver and the memory and configuredto: initiate an upload of the entirety of the progressive encoded fileto an external device; receive an indication from the external device ofwhether a low resolution version of the electrographic waveformrepresents a clinically significant event; discontinue the upload of theentirety of the progressive encoded file to the external deviceresponsive to an indication that the low resolution version of theelectrographic waveform does not represent a clinically significantevent; and complete the upload of the entirety of the progressiveencoded file to the external device responsive to an indication that thelow resolution version of the electrographic waveform does represent aclinically significant event.
 2. The implantable medical device of claim1, wherein the low resolution version of the electrographic waveformcorresponds to a portion of the entirety of the progressive encodedfile.
 3. The implantable medical device of claim 1, further comprising:one or more electrodes configured to sense electrical activity of abrain; and wherein the electrographic waveform represents the sensedelectrical activity of the brain.
 4. The implantable medical device ofclaim 3, further comprising: a detection subsystem coupled to the one ormore electrodes and configured to detect neurological activityindicative of a seizure, an onset of a seizure, or a precursor to aseizure, from the sensed electrical activity of the brain.
 5. Theimplantable medical device of claim 4, further comprising a compressionmodule coupled between the detection subsystem and the memory andconfigured to: receive, from the detection subsystem, data correspondingto the electrical activity of the brain, and create the progressiveencoded file for storage in the memory.
 6. A method of transmitting anelectrographic waveform stored in a memory of an implantable medicaldevice as a progressive encoded file, said method comprising:initiating, at the implantable medical device, an upload of the entiretyof the progressive encoded file from the implantable medical device toan external device; receiving, at the implantable medical device, anindication from the external device of whether a low resolution versionof the electrographic waveform represents a clinically significantevent; discontinuing, at the implantable medical device, the upload ofthe entirety of the progressive encoded file to the external deviceresponsive to an indication that the low resolution version of theelectrographic waveform does not represent a clinically significantevent; and completing, at the implantable medical device, the upload ofthe entirety of the progressive encoded file to the external deviceresponsive to an indication that the low resolution version of theelectrographic waveform does represent a clinically significant event.7. The method of claim 6, wherein the low resolution version of theelectrographic waveform corresponds to a portion of the entirety of theprogressive encoded file.
 8. The method of claim 6, wherein the uploadis initiated in response to an interrogation by the external device. 9.The method of claim 6, wherein the progressive encoded file is based ona full resolution version of the electrographic waveform.
 10. The methodof claim 6, further comprising: sensing, at the implantable medicaldevice, electrical activity of a brain, wherein the electrographicwaveform represents the sensed electrical activity of the brain.
 11. Themethod of claim 10, further comprising: detecting, at the implantablemedical device, neurological activity indicative of a seizure, an onsetof a seizure, or a precursor to a seizure, from the sensed electricalactivity of the brain.
 12. The method of claim 10, further comprising:creating, at the implantable medical device, the progressive encodedfile for storage in the memory based on data corresponding to the sensedelectrical activity of the brain.